Strassel Investors buys real estate, develops it, and resells it for a profit. A new property is available, and Bud Strassel, the president and owner of Strassel Investors, believes if he purchases and develops this property it can then be sold for $160,000. The current property owner has asked for bids and stated that the property will be sold for the highest bid in excess of $100,000. Two competitors will be submitting bids for the property. Strassel does not know what the competitors will bid, but he assumes for planning purposes that the amount bid by each competitor will be uniformly distributed between $100,000 and $150,000.

Develop a worksheet that can be used to simulate the bids made by the two competitors. Strassel is considering a bid of $130,000 for the property. Using a simulation of 1000 trials, what is the estimate of the probability Strassel will be able to obtain the property using a bid of $130,000? Round your answer to 1 decimal place. Enter your answer as a percent. ___________%

Use the simulation model to compute the profit for each trial of the simulation run. With maximization of profit as Strassel’s objective, use simulation to evaluate Strassel’s bid alternatives of $130,000, $140,000, or $150,000. What is the recommended bid, and what is the expected profit? A bid of $140,000 results in the largest mean profit of $ _________________.

PROBLEM 3

The average grade point average (GPA) of undergraduate students in New York is normally distributed with a population mean of 2.8 and a population standard deviation of 0.75

(I) The percentage of students with GPA's between 2 and 2.5 is

CHOICE =

(II) The percentage of students with GPA's above 3.0 is:

PERCENTAGE =

(III) Above what GPA will the top 5% of the students be (i.e., compute the 95th percentile):

GPA =

(IV) If a sample of 25 students is taken, what is the probability that the sample mean GPA will be between 2.8 and 2.75?

CHOICE =

1. Nonparametric tests should not be used when ______.

the dependent variables are ordinal scales

the assumptions of parametric tests are met

the associations being tested involve categorical variables

the population distribution is heavily skewed

2. Chi-square tests are used to analyze ______.

continuous variables

frequency of data

skewness

medians

3. The ______ tests are more powerful than the ______ tests, which means the ______ is higher for nonparametric tests.

nonparametric; parametric; type II error

parametric; nonparametric; type I error

nonparametric; parametric; type I error

parametric; nonparametric; type II error

4. Expected frequencies are obtained in rows-by-columns table assuming that the row and column categorizations are ______.

related to each other

independent of each other

equal

dependent on each other

5. Which of the following is a possible null hypothesis for a chi-square test?

The two categorical variables are unrelated in the population.

The means of populations in two independent groups are equal.

The distribution of scores for the first population is different from the distribution of scores for the second population.

The two categorical variables are related in the population.

6. If you have a 5 × 5 frequency table, then the critical value of chi-square would be based on ______ degrees of freedom.

10

8

25

16

7. The degrees of freedom of the chi-square test depend on ______.

number of cells

sample size and number of cells

number of columns, number of rows, and sample size

number of columns and number of row

8. If the results of a study using the chi-square tests are summarized as χ²(2, N = 40) = 3.31, p > .05, then you would know that the total number of participants was ______.

44

11

10

40

9. What is the critical value for chi-square when alpha = 0.05 and the degrees of freedom are 11?

19.68

11.08

24.72

26.57

10. If the results of a study using the chi-square tests are summarized as χ²(1, N = 360) = 10.11, p < .01, then you would know that it was a ______ study.

2 X 2

2 X 3

1 X 3

3 X 3

Giving a test to a group of students, the grades and gender are summarized below

If one student was chosen at random,

find the probability that the student was female.

this is the full question sorry

thanks

Many regions in North and South Carolina and Georgia have experienced rapid population growth over the last 10 years. It is expected that the growth will continue over the next 10 years. This has motivated many of the large grocery store chains to build new stores in the region. The Kelley’s Super Grocery Stores Inc. chain is no exception. The director of planning for Kelley’s Super Grocery Stores wants to study adding more stores in this region. He believes there are two main factors that indicate the amount families spend on groceries. The first is their income and the other is the number of people in the family. The director gathered the following sample information.

1. Develop a correlation matrix. (Round your answers to 3 decimal places. Negative amounts should be indicated by a minus sign.)

2. Determine the regression equation. (Round your answer to 3 decimal places.)

The regression equation is: Food = ____ + _____ income + _____ size

3. How much does an additional family member add to the amount spent on food? (Round your answer to the nearest dollar amount.)

Another member of the family adds _________ to the food bill.

4. What is the value of R²?

5. Complete the ANOVA (Leave no cells blank - be certain to enter "0" wherever required. Round SS, MS to 4 decimal places and F to 2 decimal places.)

6. State the decision rule for 0.05 significance level. H₀: = β₁ = β₂ = 0; H₁: Not all β_i's = 0.

7. Complete the table given below. (Leave no cells blank - be certain to enter "0" wherever required. Round Coefficient, SE Coefficient, P to 4 decimal places and T to 2 decimal places.)

Engineers concerned about a tower's stability have done extensive studies of its increasing tilt. Measurements of the lean of the tower over time provide much useful information. The following table gives measurements for the years 1975 to 1987. The variable "lean" represents the difference between where a point on the tower would be if the tower were straight and where it actually is. The data are coded as tenths of a millimeter in excess of 2.9 meters, so that the 1975 lean, which was 2.9644 meters, appears in the table as 644. Only the last two digits of the year were entered into the computer.

Year 75 76 77 78 79 80 81 82 83 84 85 86 87

Lean 644 646 657 668 675 690 698 700 715 718 726 743 759

(a) Plot the data. Consider whether or not the trend in lean over time appears to be linear. (Do this on paper. Your instructor may ask you to turn in this graph.) (b) What is the equation of the least-squares line? (Round your answers to three decimal places.) y = + x What percent of the variation in lean is explained by this line? (Round your answer to one decimal place.) % (c) Give a 99% confidence interval for the average rate of change (tenths of a millimeter per year) of the lean. (Round your answers to two decimal places.) ( , )

2. Your local grocery store claims that on average their fresh caught salmon will weigh 2 pounds. You want to test to see if their claim is correct so you gather a simple random sample of 45 packages of their fresh caught salmon, weigh each package, and find that the average weight of these packages is 1.76 pounds. Based on years of data, the grocery store determined that the standard deviation ? = 0.08 pounds. What is the probability of obtaining the sample that you got? Do you think the grocery store is wrong to say that on average their packages of salmon weigh 2 pounds? Why or why not?

John knows that monthly demand for his product follows a normal distribution with a mean of 2,500 units and a standard deviation of 425 units. Given this, please provide the following answers for John.

a. What is the probability that in a given month demand is less than 3,000 units?

b. What is the probability that in a given month demand is greater than 2,200 units?

c. What is the probability that in a given month demand is between 2,200 and 3,000 units?

d. What is the probability that demand will exceed 5,000 units next month?

e. If John wants to make sure that he meets monthly demand with production output at least 95% of the time. What is the minimum he should produce each month?

Show in excel with formulas

Spertus et al. performaed a randomized single blind study for subjects with stable coronary artery disease. They randomized subjects into two treatments groups. The first group had current angina medications optimized and the second group was tapered off existing medications and then started on long-acting diltiazem at 180mg/day. The researchers performed several tests to determine if there were significant differences in the two treatment groups at baseline. One of the characteristics of interest was the difference in the percentages of subjects who had reported a history of congestive heart failure. In the group where current medications were optimized, 16 of 49 subjects reported a history of congestive heart failure. The subjects placed on the diltiazem, 12 of the 51 subjects reported a history of congestive heart failure. What is the hypothesis and the conclusion?

Suppose the weights of Farmer Carl's potatoes are normally distributed with a mean of 8.2 ounces and a standard deviation of 1.3 ounces.

(a) If 4 potatoes are randomly selected, find the probability that the mean weight is less than 10.0 ounces. Round your answer to 4 decimal places.

(b) If 6 potatoes are randomly selected, find the probability that the mean weight is more than 9.6 ounces. Round your answer to 4 decimal places.

Determine the factorization method and MLE of gamma distribution

Pay your taxes: According to the Internal Revenue Service, the proportion of federal tax returns for which no tax was paid was =p0.326. As part of a tax audit, tax officials draw a simple sample of =n140 tax returns. Use Cumulative Normal Distribution Table as needed. Round your answers to at least four decimal places if necessary.

Part 1 of 4

(a)What is the probability that the sample proportion of tax returns for which no tax was paid is less than 0.29?

Part 2 of 4

(b)What is the probability that the sample proportion of tax returns for which no tax was paid is between 0.36 and 0.43?

Part 3 of 4

(c)What is the probability that the sample proportion of tax returns for which no tax was paid is greater than 0.32?

Part 4 of 4

(d)Would it be unusual if the sample proportion of tax returns for which no tax was paid was less than 0.23?

Descriptive statistics: What do all of those numbers mean in terms of the problem. Organizing and summarizing data is called descriptive statistics. Two ways to summarize data are by graphing and by using numbers (for example, finding an average). A statistical graph is a tool that helps you learn about the shape or distribution of a sample or a population. Our data is examining the distance (miles) between twenty retail stores, and a large distribution center The Mean: (84.05 miles) shows the arithmetic mean of the sample data. Standard E: (7.71822 miles) shows the standard error of the data set, which is the difference between the predicted value and the actual value. Median: (86.5 miles) shows the middle value in the data set, which is the value that separates the largest half of the values from the smallest half of the values Mode: (96 miles) shows the most common value in the data set. Standard [: (34.51693 miles) shows the sample standard deviation measure for the data set. Sample Va: (1191.418 miles) shows the sample variance for the data set, the squared standard deviation. Kurtosis: (-0.48156 miles) shows the kurtosis of the distribution. Skewness: (0.210738 miles) shows the skewness of the data set’s distribution. Range: (121 miles) shows the difference between the largest and smallest values in the data set. Minimum: ( 29 miles) shows the smallest value in the data set. Maximum: (150 miles) shows the largest value in the data set. Sum (1681 miles) adds all the values in the data set together to calculate the sum. Count (20 miles) counts the number of values in a data set.

-Identify why you choose to perform the statistical test (Sign test, Wilcoxon test, Kruskal-Wallis test).

-Identify the null hypothesis, Ho, and the alternative hypothesis, Ha.

-Determine whether the hypothesis test is left-tailed, right-tailed, or two-tailed.

-Find the critical value(s) and identify the rejection region(s).

-Find the appropriate standardized test statistic. If convenient, use technology.

-Decide whether to reject or fail to reject the null hypothesis.

-Interpret the decision in the context of the original claim.

A weight-lifting coach claims that weight-lifters can increase their strength by taking vitamin E. To test the theory, the coach randomly selects 9 athletes and gives them a strength test using a bench press. Thirty days later, after regular training supplemented by vitamin E, they are tested again. The results are listed below. Use the Wilcoxon signed-rank test to test the claim that the vitamin E supplement is effective in increasing athletes' strength. Use α = 0.05.